WO2008/151802 (Reference: FN-174) and WO2011/069698 (Reference: FN-352) disclose correlating profiles for respective image frames in a video sequence to determine relative movement between the image frames—the movement comprising either camera movement or subject movement. Providing a global measure of frame-to-frame motion however, has limited application.
Thus, it can be useful to provide information indicating both global and local motion within blocks or regions of an image sequence. There are many methods of motion estimation that use a hierarchical approach to find local block motion in a sequence of video frames.
There are two typical approaches:                Image Pyramids, for example as disclosed in U.S. Pat. No. 6,459,822, where the image is decomposed into a so called Gaussian pyramid where each level of the pyramid is a downscaled version of the previous level. A usual scale factor between levels is 2. The displacement between corresponding blocks is found by correlating pixel values between blocks. Apart from the amount of memory that is needed to store the image pyramid, this is a computationally intensive process, even if employing a small search radius.        Variable block size, where an image is kept in its original size but the search blocks get smaller with every search iteration and also the search radius is reduced, allowing for more precise estimation. The problem with this approach is that image pixels have to be accessed multiple times and numerical complexity of each iteration is high.        
U.S. Pat. No. 8,200,020 B1 discloses a computing device selecting a source tile from a source image. From the source tile, the computing device may select a first rectangular feature and a second rectangular feature. Based on the first and second rectangular features, the computing device may calculate a source feature vector. The computing device may also select a search area of a target image, and a target tile within the within the search area. Based on the target tile, the computing device may calculate a target feature vector. The computing device may determine that a difference between the source feature vector and the target feature vector is below an error threshold, and based on this determination, further determine a mapping between the source image and the target image. The computing device may then apply the mapping to the source image to produce a transformed source image.
U.S. Pat. No. 6,809,758 discloses stabilizing a motion image formed using a sequence of successive frames which includes calculating a motion vector field between adjacent frames; forming a motion vector histogram from horizontal and vertical components of the motion vector field; applying a threshold to the motion vector histogram to produce a thresholded motion vector histogram; generating average horizontal and vertical motion components from the thresholded motion vector histogram; filtering the average horizontal and vertical motion components over a number of frames to identify unwanted horizontal and vertical motion components for each of the frames; and stabilizing the image sequence by shifting each frame according to the corresponding unwanted horizontal and vertical motion.